Multiple antennas are an important means to improve the performance of wireless telecommunication systems. It is widely understood that in a system with multiple transmit and receive antennas (Multiple-Input-Multiple-Output (MIMO) channel), the spectral efficiency is much higher than the spectral efficiency of conventional single-antenna channels.
Traditionally, multiple antennas have been used to increase diversity to combat channel fading. In case of a so called 2×2 MIMO system, wherein both the transmitter and the receiver comprises two antennas, each pair of transmit and receive antennas provides a signal path from the transmitter to the receiver. By sending signals that carry the same information through different paths, multiple independently faded replicas of one and the same data symbol can be obtained at the receiver end. Thereby, a more reliable reception can be achieved. The corresponding data transmission mode, wherein a single data stream is transmitted over a MIMO channel comprising different radio transmission paths is called (single stream) diversity mode.
However, in particular if the quality of the radio link between the transmitter and the receiver is quite good, independent information can be transmitted via different channels of a MIMO connection between the transmitter and the receiver. By transmitting independent information streams in parallel through different spatial MIMO channels, the data rate can be increased. This effect is also called spatial multiplexing.
In summary, a MIMO system can provide two types of gains with respect to a data throughput between the transmitter and the receiver: a diversity gain and a spatial multiplexing gain. Therefore, a proper spatial transmit mode selection is a key concept for MIMO communication systems.
In the publication by L. Zheng and D. Tse “Diversity and Multiplexing: A Fundamental Tradeoff in Multiple-Antenna Channels”, IEEE Transactions on Information Theory, vol. 49, no. 5, pp. 1073-1096, May 2003 it has been proposed to combine the diversity gain and the spatial multiplexing gain with each other. There is an elementary trade-off between diversity and spatial multiplexing for MIMO radio communication systems. When combining a diversity transmission mode with a spatial multiplexing transmission mode, out of the total resource of transmitting and receiving antennas r transmitting and r receiving antennas can be used for data transmissions by means of spatial multiplexing of m data streams being transmitted simultaneously. The remaining r-m transmitting and r-m receiving antennas can be used for increasing the diversity of the data transmission. The diversity-multiplexing tradeoff is essentially the tradeoff between the error probability and the data rate of a MIMO radio communication system.
The major task of the medium access layer (MAC layer) in a MIMO radio communication system is to operate the multi-antenna radio link in the right balance between diversity and multiplexing. Therefore, one observes the time- and frequency-selective channel and interference conditions at the receiving user equipment (UE) and feeds this information back to the transmitting base station (BS) on a regular basis. In order to reduce the amount of feedback to be transmitted, the UE only feeds back channel quality information (CQI) on its m best radio transmission resources, which are also called physical resource blocks (PRB). The corresponding CQI for the m best PRB's are called top-m-CQI. The CQI is quantized by taking the signal to interference and noise ratio (SINR) of the respective MIMO channel into account. The BS decides upon the received CQI value on the modulation and coding scheme (MCS) to be used for a given PRB.
In this application a feedback design for the integration of multi-user MIMO in cellular mobile radio communication systems will be considered. The feedback is given by the UE's, which report beam indices referring to a set of fixed pre-coding beams and the corresponding SINR for different supported spatial transmission modes. In this respect a set of fixed pre-coding beams is defined by an orthogonal set of beamforming vectors each corresponding to a spatial electromagnetic radiation pattern. Thereby, the number of all beamforming vectors represents the number of possible radio reception alternatives for a UE. Out of the total number of radio reception alternatives a UE may select one allowing for the best radio connection quality.
In known MIMO telecommunication systems a CQI feedback is calculated for each spatial radio transmission mode and for each PRB at the UE. In the following a 2×2 MIMO communication system is considered, which means that both BS and UE have two transmitting/receiving antennas. The effective per beam SINRs are calculated for single-stream and for dual-stream transmissions. A full feedback system therefore requires three CQI values for each PRB in a system with two serving beams: two CQI values for the dual-stream case and one CQI value for the single-stream case. In this respect it is noted that in the case of single-stream data transmission, only (a) the higher CQI value corresponding to the beam pattern/beamforming vector providing for the better radio connection and (b) an identifier identifying the better beam pattern/beamforming have to be fed back from the UE to the BS. For a full flexibility at the BS both CQI values have to be fed back.
It can be easily understood that with a growing number of transmitting/receiving antennas the amount of CQI feedback information grows and, if the number of scheduled PRBs per UE is high, the resulting feedback overhead within a MIMO radio telecommunication system may become quite large.
Current third generation (3G)-MIMO-telecommunication networks relying on Orthogonal Frequency Division Multiplex (OFDM) such as for instance 3G-Long Term Evolution (LTE) networks or Worldwide Interoperability for Microwave Access (WiMAX) networks support a fixed quantization scheme for providing the feedback information between the UE and the BS. As a consequence the number of CQI feedback bits can only be reduced by (a) taking a coarser quantization scheme and/or by (b) a reduction of the parameter m defining the number of the best radio transmission resources (the number of the top-m-CQI is reduced).
(a) Taking a coarser quantization scheme would result in a large system performance decrease especially for UEs being located at the cell-edge. This has been shown in the publication by V. Jungnickel, L. Thiele, T. Wirth, M. Schellmann, T. Haustein, V. Venkatkumar, “Feedback Design for Multi-User MIMO Systems”, 13th International OFDM-Workshop (InOWo), Hamburg, Germany, August 2008. FIG. 3, which is taken from that publication, depicts the spectral data throughput (in bits per second per hertz) as a function of the number of bits which number is used for a feedback CQI.
The circles show measurement results which have been obtained for a telecommunication network comprising only one cell. The squares show simulation results for a multi-cell telecommunication network.
The open circles and squares show the spectral data throughput averaged over all UEs, i.e. UEs being located at the cell edge and UEs being located within the center of the cell. The full circles and squares show the spectral data throughput specifically for those UEs which are located at the cell edge and which typically have a comparatively small SNIR radio connection to their serving base station.
It can be seen from FIG. 3 that for cell-edge UEs, which usually suffer from a comparatively low SINR, at least 5 feedback bits are necessary for an adequate cell-edge UE support. If 5 bits are used for feedback quantization, 2 bits can be used for a modulation mode quantization, e.g. no modulation at all, Quadrature Phase Shift Keying (QPSK), 16-quadrature amplitude modulation (QAM), 64-QAM, and the code rate can be quantized with remaining 3 bits.
It can be further seen from FIG. 3 that when averaging over cell-edge UEs and center UEs the spectral data throughput is much less sensitive to the number of bits used for the CQI.
(b) A reduction of m in the top-m-CQI results in less PRBs that can be scheduled to a UE. As a consequence there is a strong performance decrease for the UE.
There may be a need for reducing the feedback overhead in a radio telecommunication network.